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8 slides25:34EN
Matthew Berman· Jul 8, 2026Anthropic’s J-Space Research: What Its Experiments Reveal and What Remains UnknownMatthew Berman · Forward FutureMatthew Berman examines experiments on internal representations in Claude, from causal interventions to safety auditing and the limits of consciousness claims.Model InterpretabilityAI researchAI Safety+2
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Matthew Berman· Jul 8, 2026What Anthropic’s J-Space Research Suggests About AI ReasoningMatthew Berman · Forward FutureMatthew Berman discusses internal model representations, interventions and the question of consciousness, while the research itself describes important limits.Model InterpretabilityReasoning & test-time computeConsciousness & Intelligence
7 slides28:11EN
Theo - t3․gg· Jul 7, 2026The Tradeoffs of Running Open-Weight AI Models LocallyTheo Browne · Ping LabsTheo Browne separates the value of open weights from the hardware, concurrency and cost constraints of local inference.Local inferenceOpen-weight modelsAI cost & performance+2
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Theo - t3․gg· Jul 7, 2026Theo Asks Why Teams Need a Separate System for Environment FilesTheo Browne · Ping LabsA brief prompt to reconsider how development teams share environment configuration.Developer workflows & testingSecurity & safetySoftware engineering
55:19EN
Sequoia Capital· Jul 7, 2026PodcastThe drone is 15% of Zipline: 140 million miles, zero incidentsKeller Rinaudo Cliffton and Eric Watson explain why the aircraft is the small part of an automated logistics system now cheaper than a car.Infrastructure & deploymentRoboticsAutonomous Systems+3
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Matthew Berman· Jul 7, 2026Claude Fable 5 Access Extended Through July 12, 2026Matthew Berman · Forward FutureMatthew Berman reports a short extension for paid Claude subscribers, without a reset of their existing usage quota.Models & training
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Matthew Berman· Jul 7, 2026Model Routing for AI Coding: A Worked Cost ExampleMatthew Berman · Forward FutureMatthew Berman separates planning, implementation and review to explain how different models can fit different tasks.AI cost & performanceAgent engineeringDeveloper productivity
4:41EN
Jane Street· Jul 6, 2026Inside Jane Street’s Internship: Projects, Mentorship and LearningCody · Jane StreetInterns and employees describe collaborative interviews, learning finance from the basics, and working on projects used by the firm.CareersCompany CultureMachine Learning+1
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Theo - t3․gg· Jul 6, 2026Theo on Markdown Files as Instructions for Coding AgentsTheo Browne · Ping LabsA short observation about how agent tools can change the scale of a software idea.Coding agentsProduct StrategyAgent engineering
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20VC with Harry Stebbings· Jul 6, 2026Podcast · 2 speakersMike Mignano on AI Applications, Open Models and Venture StrategyGuest Mike Mignano · Host Harry StebbingsThe USV partner discusses AI agents, token spending and the opportunities and risks for startups building above the model layer.Venture CapitalAI StrategyAI agents+2
8 slides43:15EN
Theo - t3․gg· Jul 6, 2026Theo’s Fable 5 Workflow: Model Routing, PR Review, and VerificationTheo Browne · Ping LabsA practical walkthrough of delegating tasks across models and turning a stalled backlog into reviewed work, with cost and deployment boundaries.Coding agentsAgent orchestrationDeveloper workflows & testing+2
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20VC with Harry Stebbings· Jul 4, 2026Podcast · 2 speakersSierra Co-founder Clay Bavor on Open Models, Enterprise AI and Building TeamsGuest Clay Bavor · Host Harry StebbingsBavor discusses model selection and compute costs, deploying AI agents for enterprises, and how Sierra approaches hiring and company culture.Enterprise AIOpen-weight modelsAI agents+2
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Cognitive Revolution "How AI Changes Everything"· Jul 4, 2026Podcast19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipHost Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.Models & trainingLocal inferenceScaling Laws+3
7 slides23:24EN
Theo - t3․gg· Jul 4, 2026Fable 5: Theo’s Take on Fallbacks, Subscription Limits, and CostTheo Browne · Ping LabsTheo Browne examines performance claims and shares the cost-saving workflow he used during a limited subscription window.Coding agentsSafety & governanceAI cost & performance+2
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Theo - t3․gg· Jul 3, 2026Theo on the AI Bubble and the Value Beneath ItTheoTheo thinks AI is in a bubble, but says its underlying value remains an open question. He contrasts NFTs with the internet and its dot-com bust.AI StrategyInvesting
4 slides38:05EN
Theo - t3․gg· Jul 3, 2026Why Theo Moved His Agent Work to Linux MachinesTheoLong-running coding agents, laptop CPU load and slow small-file operations led Theo to build a networked fleet. He demonstrates SSH, a hardware KVM and T3 Code for remote work.Coding agentsDeveloper workflows & testingInfrastructure & deployment+1
9 slides18:02EN
AI Explained· Jul 2, 2026Fable 5 and GPT-5.6 Sol: An Early Look at Capability, Price and SafetyWith Sol still in limited preview, AI Explained compares the available system cards and examines access restrictions and safety tradeoffs.Models & trainingBenchmarksAI Safety+1
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20VC with Harry Stebbings· Jul 2, 2026Podcast · 3 speakers20VC Roundtable: AI Spending, Model Competition and Software AcquisitionsGuest Jason Lemkin, Rory O’Driscoll · Host Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate enterprise AI returns, prediction markets, SaaS roll-ups and the cost of raising capital.AI cost & performanceVenture CapitalEnterprise AI+2
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No Priors: AI, Machine Learning, Tech, & Startups· Jul 2, 2026Podcast · 2 speakersTwo Years and Four Months to a Live Reactor: Valar Atomics Wants Energy Ten Times CheaperHost Sarah Guo, Elad GilIsaiah Taylor walks Sarah Guo through Ward 250 in Utah and argues that nuclear is a hardware-iteration problem, not a paper-design one.Infrastructure & deploymentCompany BuildingSafety & governance+3
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Cognitive Revolution "How AI Changes Everything"· Jul 1, 2026PodcastFrom 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can ExploreHost Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.Enterprise & strategyFine-tuningAgent orchestration+3
6 slides28:37EN
Theo - t3․gg· Jul 1, 2026Theo Tests Sonnet 5 and Explains Fable’s ReturnTheoTheo compares model benchmarks and his own coding tests, finding promise in Sonnet’s subagent orchestration but questioning its task costs.AnthropicCoding agentsAgent orchestration+2
2 slides2:19EN
Theo - t3․gg· Jul 1, 2026Theo on Sonnet 5: Agent Orchestration and Token CostsTheoTheo welcomes Sonnet 5's ability to coordinate subagents while questioning its token efficiency. He also discusses the introductory pricing announced at release.AnthropicCoding agentsAgent orchestration+1
6 slides31:30EN
Theo - t3․gg· Jun 30, 2026Why Some AI Models Use Fewer Tokens to Solve a TaskTheoTheo explains input, output, caching and reasoning tokens, then explores a hypothesis about terse internal reasoning.AI cost & performanceReasoning & test-time computeKV caching & prefix reuse+2
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Theo - t3․gg· Jun 30, 2026Theo on Shared AI Conversations and Team CollaborationTheoA shared Claude conversation in Slack lets teammates see and continue the same work. Theo argues that this kind of collaboration differs from a GitHub-centered workflow.Human-AI CollaborationDeveloper workflows & testing
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